An important consideration in the design of any communication system is the ability to assess the performance of the system while it is in operation. In digital communication systems, the ultimate criterion of performance of a data transmission link is the probability of error, often expressed in terms of the BER. As an element of an adaptive communication system BER estimation can be used to optimize receiver performance by adaptive changes of receiver parameters. In “Techniques for estimating the bit error rate in the simulation of digital communication systems” by M. C. Jeruchim, IEEE J. Sel. Areas Commmun., vol. 2, pp. 153-170, January 1984. and in “Simulation of Communication Systems”, by M. C. Jeruchim, P. Balaban, and K. S. Shanmugan, New York: Plenum Press, 1992, ch. 5, authors mention that a factor of 2 is a reasonable uncertainty for BER estimation. Consequently, the inventors of this patent believe that error rate estimation accurate within a factor 3 (cf. FIGS. 10 to 12) appears to be satisfactory for most applications, and for adaptive systems even a weak but monotonic estimator might be sufficient.
Based on operational conditions off-line and on-line monitoring are distinguished. This invention is related to On-line monitoring.
On-line monitoring comprises the following classes among others:                signal parameter measurement        path metrics processing in trellis based decoding        
The performance of digital communication systems is a complex function of many signal parameters. Some of these parameters have a direct relationship to the BER while others are more qualitative. A well-known and quantitative method is to analyze the eye pattern. The feature of the eye pattern is the separation of the received signals into one of several levels at the sampling time. Noise and distortion will make the signal vary at the sampling time and thus decrease the separation between levels. A good example of this technique is the measurement of height and width of the eye (E. A. Newcombe and S. Pasupathy, “Error Rate Monitoring For Digital Communications”, IEEE Proceedings, Vol. 70, no. 8, pp. 805-828, 1982). While the height of the eye indicates the margin against disturbances in the signal amplitude, the width of the eye shows the margin for timing variations, which may be just as important to performance.
Related is a method disclosed in U.S. Pat. No. 5,325,397 “Error rate monitor” to determine a discrete estimate of the probability density function of a decision variable e.g. received amplitude and to determine the estimated BER by similarity comparison with stored probability density functions, each associated with some BER.
A maximum-likelihood sequence detector using the Viterbi Algorithm bases its bit decisions on probabilistic decision variables (branch and path metrics differences) that are ultimately related to conditional probabilities of observing a given received signal when a given symbol or symbol sequence has been sent. The well-known Viterbi algorithm is described in several publications e.g. S. Benedetto and E. Biglieri, “Principles of Digital Transmission: With Wireless Applications”, Kluwer Academic/Plenum Publishers, 1999.
The Viterbi algorithm is widely used for channel decoding of trellis codes in communication systems as well as for detection in the presence of ISI (“equalization”) (G. D. Forney, Jr., “The Viterbi Algorithm”, IEEE Proceedings, Vol. 61, pp. 268-278, 1973). In the 151 context, some may consider the term “detector” to be more appropriate. For practical reasons, the decoder may be designed such that the information bits associated with a branch on a survivor path at time t can be released when the decoder begins operation on the branches at time t+D (S. B. Wicker, “Error Control Systems for Digital Communication and Storage”, Prentice Hall, 1995). D is the decoding depth, and is usually set to be five to ten times the constraint length of the code or the “memory” of the channel. An information-sequence error that occurs as a result of the release of information bits before the entire received sequence or stream has been decoded is called a truncation error. At low signal-to-noise ratio, the probability of truncation error is negligible for D≧6M, where M is the maximal memory order. We will hereinafter refer to the truncation mode Viterbi decoding as standard Viterbi decoding (SVD).
The achievable speed of standard Viterbi decoding is limited by the nonlinear Add-Compare-Select (ACS) recursion, which cannot be parallelized. It was shown (G. Fettweis and H. Meyr, “High-Speed Parallel Viterbi Decoding: Algorithm and VLSI-Architecture”, IEEE Commun. Magaz., pp. 46-55, 1991 (later referred to as Fettweis91); H. Dawid and G. Fettweis, “A CMOS IC for Gb/s Viterbi Decoding: System Design and VLSI Implementation”, IEEE Trans. Very Large Scale Integ. Systems, vol. 4, no. 1, pp. 17-31, 1996 (later referred to as Fettweis96)) that, despite the nonlinear recursion, it is possible to parallelize the recursive Viterbi algorithm, which we will call parallel Viterbi decoding (PVD). In PVD schemes, the received sequence of symbols is usually divided into blocks and these blocks are processed in a specific, overlapping manner, basically exploiting the self-synchronizing nature of the blindly started Viterbi algorithm and the so called path merging effect.
Based on these decision variables it is possible to produce reliability information along with or instead of the decided bit stream, which e.g. is done in so-called soft-output detectors (e.g. soft output Viterbi algorithm SOVA, or maximum a posteriori probability MAP, detectors). Typically this reliability information is then used in a downstream soft-decision FEC decoder, which can provide better decoding results by making use of this reliability information.
But also in the absence of a FEC decoder, the reliability information available in a hard decision output Viterbi detector allows to estimate the rate of decision errors.
U.S. Pat. No. 5,944,844, “Method for determining connection quality in a receiver utilizing a Viterbi Decoder” uses accumulated path metric differences, i.e. the sum of decision variables and the minimum of decision variables along the decoded path in the VA (Viterbi algorithm) to estimate BER. A drawback of this method is an increase of complexity since decision variables need to be stored until the trace-back step is completed and since accumulation of decision variable introduces complexity due to a floating-point format. Apart from the disclosure to compare estimates with predetermined threshold values the U.S. Pat. No. 5,944,844 fails to expose a practical mapping from the measured observable to a BER estimate.
U.S. Pat. No. 6,141,388, “Received signal quality determination method and systems for convolutionally encoded communications channels”. Unlike the method of U.S. Pat. No. 5,944,844, rather than using decision variables accumulated along the decoded path, this invention uses only the final decision metric in a decoded frame. This final decision metric is then mapped to a BER estimate. The method is described only in connection with convolutionally encoded data streams and frame decoding. Again, there is no disclosure how to map the measured decision metrics to a BER estimate.
In the context of decoding or detection techniques utilizing the VA for optical data transmission European patent application 03002172.9 “Error rate estimation method for a receiver and receiver apparatus” suggests to determine the frequency of unreliable detection events. An unreliable detection event is defined as a decision under indifference amongst alternatives, e.g. when an output-relevant decision is made in a Viterbi detector between two alternative paths with identical metrics. This method is simple and provides very good estimation for high BER. Due to the high data rates in optical data transmission, this method is well usable down to a BER of 10−10. However, relatively long monitoring time is needed for estimating low BER. Also it is necessary to determine a calibration coefficient used in a BER estimation formula.
U.S. Pat. No. 5,768,285, “Circuit for Evaluating Bit Error Rate Performance of a Data Decoder Having a Viterbi Detector” describes a circuit for evaluating bit error rate performance of a data decoder having a Viterbi detector in the context of synchronous data channels, particularly those used in telecommunications and magnetic data recording e.g. disk drives. Statistics are computed about the Euclidean distance between the correct branch at a time n and the closest competing branch. This distance referred to as the amplitude error margin (AEM) in U.S. Pat. No. 5,768,285, is the distance between the current Viterbi decision metric and the decision boundary, which, when crossed, causes elimination of the correct path through the trellis as result of an error event. More specifically the difference between two Viterbi metrics for each state at the time n is calculated. After performing several other additions, subtractions and comparisons the resulting signal is counted and averaged over time in order to determine AEM statistics.
According to the disclosure of U.S. Pat. No. 5,878,098 “Method and Apparatus for Rate Determination in a Communications System” path metrics are used to determine the transmission data rate which may be a full, half, quarter etc. data rate. More specifically discriminant functions D12, D14, D18, D24, D28, D48 are calculated based on weighted differences of path metrics TM1, TM2, TM4, TM8 which are also referred to as total metrics in this reference. The various discriminant functions are compared to 0 and, depending on the results, a full, half, quarter or eighth rate frame is decoded provided that a cyclic redundancy check code does not indicate an error and a quality parameter is met.
It is the object of this invention to provide a more quantitative method and circuit for bit error estimation.
This object is achieved by the subject matters of the independent claims.
Preferred embodiments of the invention are the subject matters of the dependent claims.
Inventive embodiments based on equations (33) or (34) work without a priori knowledge about the type of channel. According to equations (33) or (34) the estimated BER is calculated from readily available path metrics information in a trellis-based receiver. As an advantage, it is not necessary to determine empirical or semi-empirical numerical coefficients or thresholds. The method is more complex than EP 03002172.9 but it allows more accurate estimation. As a further advantage, the BER estimation requires less monitoring time for the same accuracy. Implementation complexity can be traded against monitoring time by sub-sampling techniques during data collection.